Paper Info
Title
Representation of conceptual ETL designs in natural language using Semantic Web technology
Abstract
Extract-Transform-Load (ETL) processes constitute the back stage of Data Warehouse architectures. Several studies characterize the ETL design as a time-consuming and error-prone procedure. A critical phase in the ETL lifecycle involves the early communications and design steps that aim at producing a conceptual ETL design. Various research approaches have dealt with the conceptual modeling of ETL processes, but all share two inconveniences: they require intensive human effort from the designers to create them, as well as technical knowledge from the business people to understand them. In this paper, we focus on the second aspect and provide a method for the representation of a conceptual ETL design as a narrative, which is the most natural means of communication and does not require particular technical skills or familiarity with any specific model. Specifically, this work builds upon previously proposed techniques that automate the conceptual design by leveraging Semantic Web technology. The key idea is to map the involved data stores, either source or target, to a domain ontology and then, to use a reasoner for producing the ETL design. We discuss how linguistic techniques can be used for the establishment of a common application vocabulary. We present a flexible and customizable template-based mechanism for the representation of the ETL design as a narrative. Finally, we discuss issues related to the production of meaningful reports and we provide implementation details.
Year
DOI
Venue
2010
10.1016/j.datak.2009.08.009
Data Knowl. Eng.
Keywords
Field
DocType
etl design,particular technical skill,semantic web technology,data warehouse architecture,design step,technical knowledge,conceptual etl design,natural language,conceptual design,conceptual modeling,etl lifecycle,model specification,metadata,semantic web,ontologies,data warehouse,conceptual model,data warehouses
Data warehouse,Ontology (information science),Ontology,Data mining,Conceptual design,Semantic reasoner,Conceptual model,Computer science,Semantic Web,Natural language,Database
Journal
Volume
Issue
ISSN
69
1
0169-023X
Citations 
PageRank 
References 
20
0.83
28
Authors
3
Name
Order
Citations
PageRank
Alkis Simitsis1166594.62
Dimitrios Skoutas283355.09
Malú Castellanos335174.33